Image quality evaluation device, terminal device, image quality evaluation system, image quality evaluation method and computer-readable recording medium for storing programs

ABSTRACT

The present invention evaluates the quality of an image shot by a terminal device in a state closer to that seen with the eye. A computer evaluates the quality of an image obtained by shooting a photographic subject including a periodic pattern that fluctuates periodically in one direction. A Fourier transform unit accomplishes a two-dimensional Fourier transform on the image to obtain two-dimensional spatial frequency spectrum components. An analysis unit analyzes the resolution of the image on the basis of spectrum components of spatial frequencies included in the periodic pattern, among the two-dimensional spatial frequency spectrum components obtained by the Fourier transform unit, and analyzes the deterioration of the image on the basis of spectrum components other than these.

INCORPORATION BY REFERENCE

This application is a divisional of U.S. patent application Ser. No.13/004,619, filed Jan. 11, 2011, which claims priority to JapanesePatent Application No. 2010-004256, filed on Jan. 12, 2010, the contentsof all of which are incorporated herein by reference.

TECHNICAL FIELD

The present invention relates to an image quality evaluation device forevaluating the quality of an image taken by a terminal device such as adigital camera or a mobile phone, a terminal device equipped with thisimage quality evaluation device, an image equality evaluation systemequipped with the image quality evaluation device or the terminaldevice, an image quality evaluation method for evaluating the quality ofan image taken by a terminal device such as a digital camera or a mobilephone, and a computer-readable recording medium for storing programs tobe executed by a computer.

BACKGROUND ART

A video resolution evaluation device for evaluating the video resolutionof display devices that display videos is disclosed (refer to theUnexamined Japanese Patent Application KOKAI Publication No.2009-38431.). This video resolution evaluation device accomplishes aFourier transform on image data obtained by photographing with a cameraa burst pattern containing a periodic pattern made up of a patternrepeated N times. Furthermore, the video resolution evaluation deviceevaluates the video resolution by comparing the level and position ofthe peaks of the periodic pattern and the phase of the periodic patternwith those of the original image.

SUMMARY

In some images displayed by a terminal device such as a mobile phone,high-frequency components are emphasized by signal processing such asedge emphasis to prevent blurring of the image. In some of this kind ofimages, jaggies (zigzags created at edges), an ill effect caused byemphasizing high-frequency components, and noise and so on exist. In theaforementioned video resolution evaluation device, it is difficult toreflect jaggies and noise in the evaluation results even if the overallimage quality falls as a result of these.

In consideration of the foregoing, it is an exemplary object of thepresent invention to provide an image quality evaluation device that canevaluate the quality of an image taken by a terminal device in a statecloser to that seen with the eye, a terminal device, an image qualityevaluation system, an image quality evaluation method and acomputer-readable recording medium for storing programs.

In order to achieve the above exemplary object, the image qualityevaluation device according to a first exemplary aspect of the presentinvention is an image quality evaluation device for evaluating thequality of an image obtained by shooting a photographic subjectincluding a periodic pattern that fluctuates periodically in onedirection, wherein the image quality evaluation device includes:

a Fourier transform unit that accomplishes a two-dimensional Fouriertransform on the image to obtain two-dimensional spatial frequencyspectrum components; and

an analysis unit that, among the two-dimensional spatial frequencyspectrum components obtained by the Fourier transform unit, analyzes theresolution of the image on the basis of spectrum components of spatialfrequencies included in the periodic pattern, and analyzes thedeterioration of the image on the basis of spectrum components otherthan these.

The image quality evaluation method according to a second exemplaryaspect of the present invention is an image quality evaluation methodfor evaluating the quality of an image obtained by shooting aphotographic subject including a periodic pattern that fluctuatesperiodically in one direction, wherein the image quality evaluationmethod includes:

a Fourier transform process that accomplishes a two-dimensional Fouriertransform on the image to obtain two-dimensional spatial frequencyspectrum components; and

an analysis process that, among the two-dimensional spatial frequencyspectrum components obtained in the Fourier transform process, analyzesthe resolution of the image on the basis of spectrum components ofspatial frequencies included in the periodic pattern, and analyzes thedeterioration of the image on the basis of spectrum components otherthan these.

The program stored on a computer-readable recording medium according toa third exemplary aspect of the present invention is:

a computer-readable recording medium for storing a program forevaluating the quality of an image obtained by shooting a photographicsubject including a periodic pattern that fluctuates periodically in onedirection, this program causing a computer to function as:

a Fourier transform means that accomplishes a two-dimensional Fouriertransform on the image to obtain two-dimensional spatial frequencyspectrum components; and

an analysis means that, among the two-dimensional spatial frequencyspectrum components obtained by the Fourier transform means, analyzesthe resolution of the image on the basis of spectrum components ofspatial frequencies included in the periodic pattern, and analyzes thedeterioration of the image on the basis of spectrum components otherthan these.

BRIEF DESCRIPTION OF THE DRAWINGS

These exemplary objects and other objects and advantages of the presentinvention will become more apparent upon reading of the followingdetailed description and the accompanying drawings in which:

FIG. 1 is an oblique view of the entire composition of an image qualityevaluation system according to a first exemplary embodiment of thepresent invention;

FIG. 2 is a block diagram showing the internal composition of the mobilephone of FIG. 1;

FIG. 3A shows one example of the evaluation pattern;

FIG. 3B is a graph showing the fluctuation in the brightness of theevaluation pattern P at a cross-section along A-A′ in FIG. 3A;

FIG. 3C is a graph showing the fluctuation in the brightness of theevaluation pattern P at a cross-section along B-B′ in FIG. 3A;

FIG. 4 is a block diagram showing the functional composition of acomputer;

FIG. 5A is one example of the center part of the evaluation pattern ofFIG. 3A;

FIG. 5B is one example of the image data in the center part shot with anoptical zoom;

FIG. 5C is one example of the image data in the center part shot with adigital zoom;

FIG. 6A is a graph showing the two-dimensional frequency spectrum of theimage data in FIG. 5B;

FIG. 6B is a graph showing the two-dimensional frequency spectrum of theimage data in FIG. 5C;

FIG. 7A is the spatial frequency spectrum along a cross-section α-α′ inFIG. 6A;

FIG. 7B is the spatial frequency spectrum along a cross-section β-β′ inFIG. 6A;

FIG. 8A is the spatial frequency spectrum along a cross-section α-α′ inFIG. 6B when the nearest neighbor method is applied;

FIG. 8B is the spatial frequency spectrum along a cross-section α-α′ inFIG. 6B when the bilinear method is applied;

FIG. 8C is the spatial frequency spectrum along a cross-section β-β′ inFIG. 6B;

FIG. 9 is a flowchart for an image quality analysis evaluation processexecuted by the computer 3;

FIG. 10 shows the RGB pixel arrangement in a sensor according to asecond exemplary embodiment of the present invention;

FIG. 11A is a drawing schematically showing the action of reading out Gpixel summation in the sensor;

FIG. 11B is a drawing schematically showing the action of reading out Rpixel summation in the sensor;

FIG. 11C is a drawing schematically showing the action of reading out Bpixel summation in the sensor;

FIG. 12A is one example of the G image data output from the sensor;

FIG. 12B is one example of the R image data output from the sensor;

FIG. 13A is one example of the spatial frequency spectrum of the G imagedata;

FIG. 13B is one example of the spatial frequency spectrum of the R imagedata;

FIG. 14A shows one example of the spatial frequency spectrum along thecross-section β-β′ of FIG. 13A;

FIG. 14B shows one example of the spatial frequency spectrum along thecross-section β-β′ of FIG. 13B;

FIG. 15 is an oblique view of the entire composition of an image qualityevaluation system 100 according to a third exemplary embodiment of thepresent invention;

FIG. 16A shows one example of the image data shot by a mobile phone;

FIG. 16B shows one example of the image data shot by a mobile phone;

FIG. 17 is one example of image data in which distortion caused by MPEGdigital compression is overlaid by the movement of a background;

FIG. 18 is one example of the spatial frequency spectrum obtainedthrough a two-dimensional Fourier transform on the image data of FIG.17;

FIG. 19A is the spatial frequency spectrum along a cross-section α-α′ inFIG. 18; and

FIG. 19B is the spatial frequency spectrum along a cross-section β-β′ inFIG. 18.

EXEMPLARY EMBODIMENTS

The exemplary embodiments of the present invention are described indetail below with reference to the attached drawings.

(First Embodiment)

First, a first exemplary embodiment of the present invention isdescribed. In this embodiment, the explanation is for an image qualityevaluation system for evaluating the quality of an image shot by acamera-equipped mobile phone.

FIG. 1 shows the entire composition of an image quality evaluationsystem 100 according to the present exemplary embodiment. As shown inFIG. 1, the image quality evaluation system 100 is equipped with amobile phone 1, a display device 2 and a personal computer (hereafter,abbreviated as “computer”) 3.

The mobile phone 1 is a camera-equipped mobile phone. FIG. 2 shows theinternal composition of the mobile phone 1. As shown in FIG. 2, themobile phone 1 has a communications antenna 21, a wireless circuit 22,an encryption/decryption processing circuit 23, a mike 24, a receiver25, keys 26, a CPU (Central Processing Unit) bus 27, a memory 28, a DAC(Digital Analog Converter) 29, a speaker 30, a video I/F 31, an LCD(Liquid Crystal Display) controller 32, a video I/F 33, a display device34 and a CPU 35.

The communications antenna 21 receives radio waves transmitted throughthe air and converts these into a high-frequency electrical signal. Theconverted high-frequency electrical signal is supplied to the wirelesscircuit 22. In addition, the communications antenna 21 convertshigh-frequency electrical signals supplied from the wireless circuit 22into radio waves and transmits such.

The wireless circuit 22 demodulates high-frequency electrical signalssupplied from the communications antenna 21 and inputs the result intothe encryption/decryption processing circuit 23. In addition, thewireless circuit 22 modulates outputs signals from theencryption/decryption processing circuit 23, converting such intohigh-frequency electrical signals, and outputs these high-frequencyelectrical signals to the communications antenna 21.

The encryption/decryption processing circuit 23 executes a decryptionprocess on output signals from the wireless circuit 22. Theencryption/decryption processing circuit 23 outputs voice signals fortelephone calls obtained as a result of this decryption process to thereceiver 25. In addition, the encryption/decryption processing circuit23 outputs text data and image data obtained in a similar manner to theCPU 35.

Furthermore, the encryption/decryption processing circuit 23 executes anencryption process on voice signals from the mike 24, text data input byoperation of the keys 26 and output from the CPU 35, and image data readfrom the memory 28 and output from the CPU 35. The various types of dataobtained as a result of this encryption process are output to thewireless circuit 22 as output signals.

The mike 24 collects sound such as the user's voice, converts this intoa voice signal and outputs this to the encryption/decryption processingcircuit 23. The receiver 25 outputs audio corresponding to voice signalsfor telephone calls output from the encryption/decryption processingcircuit 23.

The keys 26 are operation keys operated by the user. The CPU bus 27 is adata bus that connects the memory 28 and the DAC 29 to the CPU 35.

Various types of control programs are stored in the memory 28. Inaddition, the memory 28 stores data such as a telephone directory and anaddress directory, ring-tone melodies, audio data such as music, andimage data such as video and still images.

The DAC 29 converts digital audio signals such as ring-tone sounds andtelephone call audio output from the CPU 35 via the CPU bus 27 intoanalog signals and supplies these to the speaker 30. The speaker 30outputs as audio the ring-tone sounds and telephone call audiocorresponding to the analog signals supplied from the DAC 29.

The video I/F 31 is an interface between the CPU 35 and the LCDcontroller 32. A CMOS parallel bus can be utilized as the video I/F 31,but a differential serial bus is typically used out of consideration ofnoise and reduction of signal line numbers.

The LCD controller 32 houses VRAM (Video RAM) 36. The VRAM 36 has thecapacity to store about one screen or two screens of images. Using theVRAM 36, the LCD controller 32 creates frame images by combining one orboth image data sent intermittently or partially from the CPU 35.Furthermore, the LCD controller 32 continuously reads this frame imageat a frequency of around 60 Hz, and outputs this to the display device34 via the video I/F 33.

The video I/F 33 may be a differential serial bus similar to the videoI/F 31, but in the present exemplary embodiment, a CMOS parallel bus isutilized as the video I/F 33.

As the display device 34, a device with a stripe format in which asingle pixel is composed of the three pixels of R (red), G (green) and B(blue) is utilized. More specifically, devices with a variety of pixelcounts can be used as the display device 34, such as QVGA (320×240×RGB),VGA (640×480×RGB), wide VGA (800×480×RGB) or full wide VGA(854×480×RGB). In the present exemplary embodiment, a VGA (640×480×RGB)is utilized. In addition, in the present exemplary embodiment, thedisplay device 34 is a liquid crystal display.

The CPU 35 reads programs from the memory 28 via the CPU bus 27, andgenerally controls the various above-described constituent elements byexecuting these programs.

For example, the CPU 35 accomplishes a detection process for theoperation contents of the keys 26. Furthermore, the CPU 35 detects theoperation contents of the keys 26, controls the wireless circuit 22 andthe encryption/decryption processing circuit 23 in accordance with thedetected key operation, and accomplishes transmission processes, voicecall processes, and music and image reproduction processes and the like.

On the other hand, the CPU 35 accomplishes processes related to waitingfor an incoming call by controlling the encryption/decryption processingcircuit 23 and the wireless circuit 22. When a call is received, the CPU35 reads the incoming call image, the ring-tone melody and the name ofthe caller from the telephone directory in the memory 28. Furthermore,the CPU 35 outputs audio data to the DAC 29 and causes the caller'stelephone number, name and image data to be displayed on the displaydevice 34 via the video I/F 31, the LCD controller 32 and the video I/F33. When talking is selected by key operation, the CPU 35 accomplishesvoice call processing.

In addition to the above constituent elements, the mobile phone 1 isfurther equipped with a camera module 40, a memory card 41 and anexternal interface (I/F) 42. The camera module 40, the memory card 41and the external I/F 42 are connected to the CPU 35.

The camera module 40 is equipped with a lens 43 and a sensor 44. Thelens 43 focuses incident light on the sensor 44. The sensor 44 convertsthe incident light into an electrical signal through photoelectricconversion. As the sensor 44, a CMOS (Complimentary Metal OxideSemiconductor) type or a CCD (Charge Coupled Device) type can be used.In general, a color type with R, G and B filters is used for each pixelof the sensor 44, but to simplify the explanation, a monochrome type isused here.

The electrical signal output from the sensor 44 is input into an ISP(Image Signal Processor) 45 that is part of the CPU 35. The ISP 45applies an A/D (Analog to Digital) conversion to the output from thesensor 44, converting this into a digital signal. A noise reductionprocess, gamma correction and a resizing process on a predeterminednumber of pixels are executed on the image data converted to a digitalsignal.

The CPU 35 displays an image based on the image data output from the ISP45 on the display device 34 via the video I/F 31, the LCD controller 32and the video I/F 33. When shooting is started by operation of the keys26, the CPU 35 digitally compresses that image data and stores it in thememory 28 or on the memory card 41. A generic type can be used as thealgorithm for this digital compression. For example, JPEG (JointPhotographic Experts Group) can be used in the case of a stillphotograph, and MPEG (Moving Picture Experts Group) can be used in thecase of video. The CPU 35 may record the image data in the memory 28 oron the memory card 41 in pre-digital-conversion data format or RGBformat.

The external I/F 42 may be capable of communicating with the computer 3.Here, a USB (Universal Serial Bus) is used. The external I/F 42 isconnected to the computer 3.

The display device 2 displays the evaluation pattern P shot by thecamera module 40 of the mobile phone 1.

FIG. 3A shows one example of an evaluation pattern P. The display device2 displays a chart on which this evaluation pattern P has been printed.FIG. 3B is a graph showing fluctuations in the brightness in theevaluation pattern P along the cross-section A-A′ in FIG. 3A. Inaddition, FIG. 3C is a graph showing fluctuations in the brightness inthe evaluation pattern P along the cross-section B-B′ in FIG. 3A. Asshown comprehensively in FIGS. 3A to 3C, the evaluation pattern P is apattern such that the brightness varies in square waveform in the A-A′direction (a first direction) inclined by 45° to the X axis, and has noperiodic fluctuation in the brightness in the B-B′ direction (a seconddirection) orthogonal to the first direction.

Image data corresponding to the evaluation pattern P photographed by themobile phone 1 is input and the computer 3 analyzes and evaluates thequality thereof. More specifically, the computer 3 performs atwo-dimensional Fourier transform on the image data obtained byphotography by the mobile phone 1, acquires the frequency spectrum ofthat image data and analyzes the image data. For example, the computer 3analyzes the resolution of the image data and whether or not jaggieshave occurred in the image data.

As shown in FIG. 4, the computer 3 is equipped with an image data inputunit 50, a Fourier transform unit 51, an analyzer 52, an evaluator 53and a display unit 54.

Image data containing the image of the evaluation pattern P photographedby the mobile phone 1 is input into the image data input unit 50. TheFourier transform unit 51 performs a two-dimensional Fourier transformon the image data input into the image data input unit 50 and obtainsthe two-dimensional spatial frequency spectrum components.

The analyzer 52 analyzes the resolution of the image on the basis of thespectrum components contained in the evaluation pattern P among thespectrum components of the two-dimensional spatial frequency obtained bythe Fourier transform unit 51, and analyzes deterioration of the imageon the basis of the spectrum components other than this.

The evaluator 53 comprehensively evaluates the quality of the image dataphotographed by the mobile phone 1 on the basis of the analysis resultsfrom the analyzer 52. The display unit 54 displays these evaluationresults.

The operation of the image quality evaluation system 100 according tothe present exemplary embodiment is described next.

The evaluation subject of the image quality evaluation system 100according to the present exemplary embodiment is image data shot afterenlarging with a zoom. Zooming formats primarily consist of opticalzooming and electronic zooming (digital zooming).

Because optical zooming changes the angle of incidence on the sensor 44by controlling the focal length of the optical system, when the centerpart Z of the evaluation pattern P is shot after enlarging throughoptical zooming, as shown in FIG. 5A, the center part Z can be shotwithout deterioration of image quality, as shown by image data P1 inFIG. 5B.

However, because optical systems have high cost and the lens modulebecomes larger with an optical zoom, in the camera module 40 of themobile phone 1, a digital zoom is employed. A digital zoom offers theadvantages of being realized compactly and at low cost, but there areconcerns that deterioration of image quality could occur due toenlargement of the image.

Hence, in the present exemplary embodiment, the action of the imagequality evaluation system 100 will be described while comparing imagesshot after enlarging with a digital zoom by the camera module 40 or thelike in the mobile phone 1 and images shot using an ideal zoom (opticalzoom).

For example, suppose that three times the image is photographed using adigital zoom. When the image is magnified three times with a digitalzoom, the number of pixels is multiplied by three by adding two pixelsfound through a filter operation on one pixel of the original image.Consequently, blurring and jaggies can occur in the image.

For example, consider the case of using the nearest neighbor method tomultiply the number of pixels by three by copying the value of the samepixel. The nearest neighbor method is a method that uses without changesthe brightness value of the pixel whose distance is physically closest.Image data enlarged three times by a digital zoom using the nearestneighbor method is image data in which jaggies occur with a period ofthree pixels on the edge as shown in the image data P2 in FIG. 5Cbecause the slanted line changes with a period of three pixels. Thisimage data is captured by the computer 3 via the memory card 41 or theexternal I/F 43. The computer 3 converts this to a frequency spectrum byperforming a two-dimensional Fourier transform, and analyzes the qualityof the image.

The computer 3 performs a two-dimensional Fourier transform on the imagedata using the following formula.

$\begin{matrix}{\left( {{Formula}\mspace{14mu} 1} \right)\mspace{625mu}} & \; \\{{F\left( {u,v} \right)} = {\frac{1}{2\pi} \cdot {\int_{- \infty}^{\infty}{\int_{- \infty}^{\infty}{{f\left( {x,y} \right)}{\mathbb{e}}^{- {{\mathbb{i}}{({{ux} + {vy}})}}}{\mathbb{d}x}{\mathbb{d}y}}}}}} & (1)\end{matrix}$

FIGS. 6A and 6B show graphs in which the frequency spectrum of the imagedata obtained by Formula (1) above is plotted in a two-dimensional plane(the u-v plane). In these graphs, the first and third quadrants and thesecond and fourth quadrants have been respectively switched in relationto the X-Y coordinate axes of the evaluation pattern P in FIG. 3A. Inaddition, in this graph the origin (center) is a direct currentcomponent and the farther out from the origin it is, in other words themore toward the perimeter it is, the higher the spatial frequency is.

FIG. 6A shows the frequency spectrum of the image shot with an opticalzoom shown in FIG. 5B. As shown in FIG. 6A, with an optical zoom, in thefrequency spectrum resulting from the two-dimensional Fourier transformthe non-zero spectrum components are expressed by the α-α′ cross-sectioncorresponding to the A-A′ direction in the evaluation pattern P (seeFIG. 3A).

The direction of the α-α′ cross-section is equivalent to the directionin which waves advance when the evaluation pattern P (periodic pattern)is thought of as waves. That the frequency spectrum appears in thesecond quadrant and the fourth quadrant by the point symmetry callingthe center the origin is because negative and positive Fourier solutionsare calculated. The computer 3 may use the spectrum components of thefrequency spectrum in either quadrant in analyzing image quality.

The frequency spectrum of the optical zoom image along the α-α′cross-section in FIG. 6A is shown in FIG. 7A. In addition, the frequencyspectrum of the optical zoom image along the β-β′ cross-section in FIG.6A is shown in FIG. 7B. In both FIGS. 7A and 7B, the vertical axisrepresents spectral intensity and the horizontal axis represents spatialfrequency.

In the case of an optical zoom, burring and jaggies do not occur at theedges of the image enlarged and photographed, so the square waveform ofthe evaluation pattern P is maintained (see image data P1 in FIG. 5B).Accordingly, letting fs be the spatial frequency of the square waveformin the evaluation pattern P, peaks in spectrum components occur at thespatial frequencies 3fs and 5fs, which coincide with the odd-orderhigh-frequency components.

On the other hand, in the image data P1 (see FIG. 5B), no periodicpattern exists in the B-B′ direction, so no spectrum components existfor the basic spatial frequency fs or the high frequency spatialfrequencies 3fs and 5fs on the β-β′ cross-section. Accordingly, only thedirect current components can be observed as spectrum components in theβ-β′ direction, as shown in FIG. 7B.

On the other hand, FIG. 6B shows the frequency spectrum of images shotusing a digital zoom. In addition, one example of the frequency spectrumof digital zoom images along the α-α′ cross-section in FIG. 6B is shownin FIGS. 8A and 8B. FIG. 8A shows the frequency spectrum when the imageis enlarged using the nearest neighbor method. In addition, FIG. 8Bshows the frequency spectrum when the image is enlarged using thebilinear method.

When the nearest neighbor method is applied, there is little blurring ofthe image, so the same frequency spectrum as in FIG. 7A can be observed,as shown in FIG. 8A. In other words, by utilizing the nearest neighbormethod, the same resolution can be obtained as in FIG. 8A.

In contrast, when the generally used bilinear method is applied, thethird-order and fifth-order high frequency components at the spatialfrequencies 3fs and 5fs become smaller because the image is blurred, asshown in FIG. 8B.

The computer 3 evaluates the resolution of the image by comparing thelevel and the position (spatial frequency) of the peaks of the spectrumcomponents of the high frequencies.

FIG. 8C shows one example of the frequency spectrum of a digital zoomimage along the β-β′ cross-section in FIG. 6B. Because the repeatedfrequency of the peaks of the repeatedly occurring jaggies is threepixels, a peak of the spectrum components caused by the jaggies appearsat the spatial frequency π/3, as shown in FIG. 8C. This spectrumcomponent cannot be seen in the spectrum of the optical zoom (see FIG.7B) that is an example of an ideal zoom, so it can be said to be thedeterioration component of the image. Thus, the computer 3 evaluates thedegree of quality deterioration caused by jaggies by finding thespectrum components of the frequency spectrum in the β-β′ direction.

FIG. 9 shows a flowchart of the image quality analysis and evaluationprocess of the computer 3. As shown in FIG. 9, first the image data sentfrom the memory card 41 or the mobile phone 1 is input into the imagedata input unit 50 (step S1). Next, the Fourier transform unit 51accomplishes a two-dimensional Fourier transform on the input image data(step S2).

Next, the analyzer 52 analyzes the spectrum components in the α-α′cross-section of the two-dimensional plane (u, v) computed from thetwo-dimensional Fourier transform (step S3). Here, the analyzer 52compares the spectrum components shown in FIG. 7A and the spectrumcomponents of the α-α′ cross-section computed from the two-dimensionalFourier transform, for example, and determines whether or not imageblurring has occurred, that is to say to analyze the resolution. Morespecifically, the analyzer 52 determines whether or not the third-orderand fifth-order high frequency components has fallen more than athreshold value.

Next, the analyzer 52 accomplishes spectral analysis of the spatialfrequency component in the β-β′ cross-section of the two-dimensionalplane (u, v) computed from the two-dimensional Fourier transform (stepS4). Here, the analyzer 52 analyzes deterioration of the image on thebasis of the spatial frequency component in the β-β′ cross-sectioncomputed from the two-dimensional Fourier transform. More specifically,the analyzer 52 determines whether or not jaggies or noise have occurredin the image by whether or not peaks exist above a predetermined levelin the spectrum components in the β-β′ cross-section. In addition, theanalyzer 52 determines whether or not jaggies have occurred in the imagebased on whether or not the peak spatial frequency is π/3 (or −π/3). Thereason π/3 is found is because the spatial frequency is ⅓ because theimage was enlarged three times.

Next, the evaluator 53 comprehensively evaluates the quality of theimage data shot by the mobile phone 1 on the basis of the analysisresults from the analyzer 52 (step S5). For example, when a peak in aspectrum component larger than a predetermined level cannot be ignoredin the part corresponding to the spatial frequency π/3 in the β-β′cross-section, the evaluator 53 evaluates the quality of the image aslow because jaggies are occurring even though the high-frequencyspectrum components at the spatial frequencies 3fs and 5fs in the α-α′cross-section have not become smaller and the image is not blurred.

Next, the display unit 54 displays the evaluation results from theevaluator 53 (step S6).

As explained in detail above, with the present exemplary embodiment, itis possible to evaluate both the resolution of the image anddeterioration of the image, and consequently it is possible to evaluatethe quality of the image shot by the mobile phone 1 in a state closer tothat seen with the eye.

More specifically, with the present exemplary embodiment, the analyzer52 analyzes whether or not the components of the evaluation pattern P inthe image data are deteriorating, by comparing the spatial frequencyspectrum of the evaluation pattern P in the α-α′ cross-section of FIG.6A that has been enlarged by an optical zoom and the spatial frequencyspectrum of image data in the α-α′ cross-section of FIG. 6B that hasbeen enlarged by an electronic zoom. Through this analysis, it ispossible to determine whether or not the image is blurred and toevaluate the resolution of the image.

In addition, the computer 3 analyzes whether or not components notincluded in the evaluation pattern P in the image (componentscorresponding to the enlargement ratio of the digital zoom) areincluded, on the basis of the frequency spectrum components in the β-β′cross-section direction. Through this analysis, it is possible todetermine whether or not jaggies or noise are occurring due to thedigital zoom, that is to say to evaluate deterioration of the image.

Through this, image quality evaluation becomes possible from theperspectives of both improvement in resolution through image qualitycorrection processing such as strengthening edges in image data expandedand shot with the digital zoom, and deterioration in image qualitycaused by increased jaggies and noise resulting from the digital zoom.As a result, it is possible to evaluate the quality of the image datashot by the mobile phone 1 in a state closer to that seen by the eye.

In the present exemplary embodiment, it is possible to detect jaggieswith high precision because spectrum components of the β-β′cross-section that does not originally have a periodic spectrumcomponent are used.

In the present exemplary embodiment, in order to simplify theexplanation one peak each is assumed to occur for the spectrumcomponents of the frequency spectrum in the first quadrant and the thirdquadrant by the jaggies caused by the digital zoom, as shown in FIG. 6B.However, in reality there are cases in which multiple peaks for spectrumcomponents occur in the first quadrant and the third quadrant. Inaddition, there are cases in which peaks for spectrum components occurin the second quadrant and the fourth quadrant as well.

In such cases, the computer 3 may take all peaks of spectrum componentsas analysis subjects, or may create a threshold value for spectralintensity and take only peaks having a spectral intensity greater thanthe threshold value as the analysis targets.

In addition, analysis may be conducted using the sum of the spectralintensities in all or some of the peaks of the spectrum components, oranalysis may be conducted using the average value of the peak values, oranalysis may be conducted on the correlation to the spectrum of theoptical zoom. In addition, analysis may also be conducted with themaximum value of the peak (the maximum spectral intensity) as therepresentative value. In addition, because even optical zoom images mayaccompany with deterioration according to optical system performance,comparison with images electronically created with no deterioration maybe accomplished.

(Second Exemplary Embodiment)

Next, the second exemplary embodiment of the present invention isdescribed. The composition and action of the image quality evaluationsystem 100 according to the present exemplary embodiment is the same asthat shown in FIGS. 1 and 9.

However, in the present exemplary embodiment, the composition of thesensor 44 of the mobile phone 1 differs. In the above-described firstexemplary embodiment, a monochrome type was used for the sensor 44 ofthe mobile phone 1, but in the present exemplary embodiment, the sensor44 has a color sensor provided with RGB color filters in each pixel.

FIG. 10 shows the RGB pixel arrangement in the sensor 44. As shown inFIG. 10, G and R are alternately positioned on the first line of thisarrangement. In addition, B and G are alternately positioned on thesecond line. Furthermore, G and R are alternately positioned on thethird line. This kind of pixel arrangement is generally called a Bayerarrangement because G is positioned in a staggered pattern on theodd-numbered lines and the even-numbered lines. The Bayer arrangementdiffers from a stripe arrangement in that the number of R and B pixelsis half the number of G pixels.

The mobile phone 1 can shoot both still images and video using thesensor 44. When shooting still images, the time gap between photographsis sufficiently long, excluding continuous shooting, so the readout timefor images from the sensor 44 is not much of a problem. Because of this,when shooting still images, it is possible to take the time to read thedata from all pixels in the sensor 44.

However, when shooting video, normally a frame rate of 30 fps (framesper second) must be maintained. In order to maintain this frame rate, itis necessary to complete the readout of image data for a single frame in1/30 of a second. Hence, in general the pixels are thinned and read outfrom the sensor 44 or the brightness values of several surroundingpixels are added and combined in a single pixel having that summed valueas brightness value and read out. Below, the case of reading out thepixel sum from the sensor 44 is explained as an example.

FIG. 11A schematically shows the action of the pixel sum readout of G inthe sensor 44. G in FIG. 11A shows the pixel position of G in the sensor44. In the action of the pixel sum readout, the four G pixels adjacentto the top and bottom and left and right are summed and output as thepixel values for the positions surrounded by bold lines. FIGS. 11B and11C schematically show the pixel sum readout action for R and B. In bothof these, the four G pixels adjacent to the top, bottom, left and rightare summed and output the summed value as the pixel value for theposition enclosed by the bold lines.

Using this kind of pixel sum readout, an example of image data when theevaluation pattern P (see FIG. 3A) is shot is shown in FIGS. 12A and12B. FIG. 12A shows one example of the G image data output from thesensor 44. In addition, FIG. 12B shows one example of the R image dataoutput from the sensor 44. The B image data output from the sensor 44 issubstantially the same as that of the R, so explanation of such isomitted here.

With the G pixel data, the horizontal and vertical resolution is ½ fromthe pixel sum, so that image data becomes an image with jaggiesoccurring in a period of two pixels, as shown in FIG. 12A. On the otherhand, the number of pixels of R image data is ¼ that of the G imagedata, so that image data becomes an image with jaggies occurring in aperiod of four pixels, as shown in FIG. 12B.

One example of a two-dimensional frequency spectrum obtained by thecomputer 3 is shown in FIGS. 13A and 13B.

FIG. 13A shows one example of the spatial frequency spectrum of the Gimage data (see FIG. 12A). Similar to the above-described firstexemplary embodiment, when the line of the evaluation pattern P isthought of as a square wave, a peak in the spectrum component of theevaluation pattern P appears in the direction in which the square waveadvances, that is to say along the α-α′ cross-section. The analyzer 52evaluates the resolution of the image by analyzing the spectrumcomponents along the α-α′ cross-section, the same as in theabove-described first exemplary embodiment.

In addition, FIG. 14A shows the spectrum components along the β-β′cross-section in FIG. 13A. The analyzer 52 evaluates deterioration ofthe image by analyzing the spectrum components along the β-β′cross-section, the same as in the above-described first exemplaryembodiment.

In the above-described first exemplary embodiment, the analyzer 52detected jaggies occurring because of digital zoom, but in the presentexemplary embodiment, jaggies caused by pixel summation of G image dataare detected. Jaggies caused by pixel summation of G image data occurwith a period of two pixels, so the analyzer 52 detects the occurrenceof jaggies caused by G pixel summation by measuring the peak of thespectrum components at the spatial frequency π/2.

On the other hand, FIG. 13B shows one example of the spatial frequencyspectrum of the R image data (see FIG. 12B). As shown in FIG. 13B, peaksof spectrum components of the evaluation pattern P are observed on theα-α′ cross-section, and spectrum components corresponding to jaggiesoccurring because of pixel summation are observed on the β-β′cross-section.

In addition, FIG. 14B shows the spectrum components on the β-β′cross-section of FIG. 13B.

Jaggies caused by pixel summation of R image data occur with a period offour pixels, so the analyzer 52 detects the occurrence of jaggies causedby R pixel summation by measuring the peak of the spectrum components atthe spatial frequency π/4.

As explained in detail above, with the present exemplary embodiment, itis possible to predict the spatial frequency where peaks of the spectrumcomponents will appear using the evaluation pattern P, so the computer 3can separately analyze spectrum components of spatial frequencies causedby pixel summation and factors other than that. In other words, evenwhen pixel summation and a digital zoom are both applied, it is possibleto do analysis while distinguishing the peaks of the spectrum componentscaused by jaggies.

Analysis of the frequency spectrum according to the present exemplaryembodiment is also possible for R, G and B image data prior to YUVconversion. For example, even with images that have undergoing YUVconversion by the ISP 45 or the CPU 35 analysis of each color R, G and Bis possible by converting to R, G and B image data using the computer 3.In addition, even with images compressed using JPEG or MPEG by the ISP45 or the CPU 35, analysis of each color is possible by converting to R,G and B image data after decompressing with the computer 3.

(Embodiment 3)

Next, a third exemplary embodiment of the present invention isdescribed.

In the above-described first exemplary embodiment, the case wasexplained wherein image quality is evaluated by paying attention tojaggies caused by the digital zoom. In addition, in the above-describedsecond exemplary embodiment the case of evaluating jaggies caused bypixel summation was explained. In contrast, in the present exemplaryembodiment, the case will be explained for evaluating distortion (blocknoise or mosquito noise) generated by digital compression.

With MPEG, an image data compression process is accomplished in blockunits called macro blocks composed of 16 pixels horizontally and 16pixels vertically. Accordingly, in this image data, distortion occursreadily in macro block units. Distortion caused by the MPEG compressionprocess can also be evaluated by frequency spectrum analysis by thecomputer 3.

FIG. 15 shows the entire composition of an image quality evaluationsystem 100 according to the third exemplary embodiment of the presentinvention. As shown in FIG. 15, the display device 2 displays anevaluation pattern R, but the evaluation pattern R is a pattern with amoving background superimposed on the evaluation pattern P that is aperiodic pattern of square waveforms in an inclined direction.

As this background, it is possible to utilize the state of a personmoving in the direction indicated by the arrow a. Through this, video isshot by the mobile phone 1 in a state in which the state of the personmoving in the direction of the arrow a is superimposed on the evaluationpattern P. Giving motion to the background image of the evaluationpattern P in this manner is because the more moving parts in the image,the more noticeable the above-described distortion becomes. Constituentelements that are the same as in the above-described exemplaryembodiments are labeled with the same reference numbers, and redundantexplanation is omitted.

One example of the image data R1 shot by the mobile phone 1 is shown inFIGS. 16A and 16B. The background person is taken to be at the positionshown in FIG. 16A at a time t1. Following this, the person moves in the“a” direction (see FIG. 15) and moves to the right side as shown in FIG.16B at a time t2. On the other hand, the evaluation pattern P displayedby the display device 2 does not move and thus is displayed at the sameposition on the screen (image P1). The evaluation pattern P is fixednear the center of the screen of the display device 2 but may be fixedat any position in the screen.

The CPU 35 of the mobile phone 1 creates an image file by compressingwith MPEG the image data shot at a frame rate of 30 fps during theinterval from time t1 to time t2, and stores the result in the memory 28or on the memory card 41. This image file is captured by the computer 3via the memory card 41 or the external I/F 42. The captured image fileis decompressed by the computer 3, a two-dimensional Fourier transformis performed on an arbitrary one frame of image data and imagecompression distortion caused by MPEG is evaluated by analyzing thefrequency spectrum.

One example of the image R2 on which the analysis process is conductedby the computer 3 is shown in FIG. 17. As shown in FIG. 17, the image R2is an image in which distortion caused by MPEG compression is overlaidon the evaluation pattern P by movement of the background. The result ofperforming a two-dimensional Fourier transform on this image data isshown in FIG. 18.

The spectrum components along the α-α′ cross-section of FIG. 18 areshown in FIG. 19A. In addition to the peaks of the spectrum componentsof the square wave similar to the above-described exemplary embodiments,a peak of the spectrum components also appears at the spatial frequencyπ/16 because of the distortion in 16-pixel units. This peak is separatefrom the peaks caused by the evaluation pattern P on the frequency axis,so it is possible to evaluate such separately from the square wave. Onthe other hand, in the spectrum components along the β-β′ cross-sectionas well, a component of distortion caused by MPEG compression appears atπ/16, as shown in FIG. 19B. The analyzer 52 evaluates compressiondistortion caused by MPEG by measuring these spectral peaks.

In the present exemplary embodiment, the case of using MPEG as thedigital compression format was explained. However, the present inventionis not restricted to this. For example, other formats such as H.264 maybe used as the digital compression method. In addition, in the case ofstill images, a digital compression format for still images such as JPEGmay be utilized.

As explained in detail above, with the present exemplary embodiment, itis possible to predict the spatial frequencies at which peaks in thefrequency spectrums occur because of distorted pixel units that shouldbe evaluated, so it is possible to evaluate by extracting only thedistortion caused by the target factor. Accordingly, even in images inwhich distortion caused by image enlargement, pixel summation and MPEGare intermixed, if the enlargement ratio, number of pixels summed andnumber of pixels in the macro block are already known, it is possible toevaluate by each factor.

In addition, when spectrum components having a peak at π/16 overlap thespectrum of the direct current components in the center and aredifficult to analyze, the size of the evaluation pattern P may bereduced or the area in the angle of view may be reduced by extending theshooting distance so that the distribution of the direct currentcomponent is reduced. In addition, the area of the image where spectralanalysis is accomplished by the computer 3 may be limited.

In addition, the size of the macro blocks is not limited to 16 pixelunits and may be set to any size in accordance with the compressionalgorithm. In this case, it is preferable for the size of the evaluationpattern P and the shooting distance to be adjusted so that the frequencyspectrum can be easily observed.

In the above-described exemplary embodiments, the direction of thesquare wave of the evaluation pattern P was 45°, but this does notnecessarily need to be 45°. In addition, the evaluation pattern P may betransmissive or reflective.

In addition, in the above-described exemplary embodiments, evaluation ofthe quality of the image data was accomplished by the computer 3, butevaluation of the quality of data in the image may be accomplished bythe mobile phone 1.

In addition, in the above-described exemplary embodiments, the displaydevice 34 was a liquid crystal display, but the display device 34 may bea self-luminescent organic EL display.

In the above-described exemplary embodiments, the terminal device wasthe mobile phone 1, but the present invention is not limited to this.For example, the terminal device may be a general terminal devicecapable of shooting video, such as a PHS (Personal Handy-Phone System),a PDA (Personal Digital Assistant), a computer, a digital camera, adigital movie or a video recording device or the like.

In the above-described exemplary embodiments, the system for executingthe above-described processes may be composed by storing the executedprogram on a computer-readable recording medium such as a flexible disk,a CD-ROM (Compact Disk Read-Only Memory), a DVD (Digital VersatileDisk), an MO (Magneto-Optical Disk) or the like and distributing thisrecording medium and installing that program.

In addition, by storing the program on a disk device possessed by aprescribed server device on a communications network such as theInternet, the program may be downloaded via carrier waves.

In addition, when the above-described functions are allocated to andrealized by an OS (Operating System) or are realized by cooperationbetween an OS and applications, the portions other than the OS may bestored on a medium and distributed, and in addition may be downloaded orthe like.

This invention is not limited by the form and the drawing of theabove-described exemplary embodiments. Of course it is possible to makea change to the form and the drawing of embodiment insofar as thesummary of this invention is not changed.

All or a portion of the above-described exemplary embodiments may benoted in the further exemplary embodiment below but are not limitedthereby.

(Further Exemplary Embodiment 1)

An image quality evaluation device for evaluating the quality of animage obtained by shooting a photographic subject including a periodicpattern that fluctuates periodically in one direction, wherein the imagequality evaluation device includes:

a Fourier transform unit that accomplishes a two-dimensional Fouriertransform on the image to obtain two-dimensional spatial frequencyspectrum components; and

an analysis unit that, among the two-dimensional spatial frequencyspectrum components obtained by the Fourier transform unit, analyzes theresolution of the image on the basis of spectrum components of spatialfrequencies included in the periodic pattern, and analyzes thedeterioration of the image on the basis of spectrum components otherthan these.

(Further Exemplary Embodiment 2)

The image quality evaluation device according to Further exemplaryembodiment 1, wherein:

the periodic pattern has a square wave shape; and

the analysis unit analyzes the resolution of the image on the basis ofspectrum components relating to a first direction corresponding to thedirection in which the periodic pattern periodically fluctuates, and

analyzes deterioration of the image on the basis of spectrum componentsrelating to a second direction orthogonal to the first direction.

(Further Exemplary Embodiment 3)

The image quality evaluation device according to Further exemplaryembodiment 1 or Further exemplary embodiment 2, wherein:

the image is an image enlarged by digital zoom, and

the analysis unit determines whether or not jaggies have occurred on thebasis of the spectrum components of spatial frequencies corresponding tothe enlargement ratio of the image.

(Further Exemplary Embodiment 4)

The image quality evaluation device according to any of Furtherexemplary embodiment 1 through Further exemplary embodiment 3, wherein:

the image is an image in which various pixels in the original image havebeen periodically thinned, or an image in which multiple pixels in theoriginal image have been periodically summed on brightness; and

the analysis unit determines whether or not jaggies have occurred on thebasis of the spectrum components of spatial frequencies corresponding tothe period of the thinning or the brightness summing.

(Further Exemplary Embodiment 5)

The image quality evaluation device according to any of Furtherexemplary embodiment 1 through Further exemplary embodiment 4, wherein:

the image is R, G and B images that make up a color image;

the Fourier transform unit obtains the two-dimensional spatial frequencyspectrum components by performing a two-dimensional Fourier transform oneach of the R, G and B images; and

the analysis unit analyzes the resolution of the image and thedeterioration of the image on the basis of the spectrum components ofthe two-dimensional spatial frequencies of each of the R, G and Bimages.

(Further Exemplary Embodiment 6)

The image quality evaluation device according to any of Furtherexemplary embodiment 1 through Further exemplary embodiment 5, wherein:

the image is an image digitally compressed by a prescribed method; and

the analysis unit determines whether or not the image has deterioratedthrough the digital compression process on the basis of the spectrumcomponents of the spatial frequencies corresponding to blocks that arecompression units of the digital compression.

(Further Exemplary Embodiment 7)

The image quality evaluation device according to any of Furtherexemplary embodiment 1 through Further exemplary embodiment 6, wherein:

the analysis unit analyzes the resolution of the image and deteriorationof the image on the basis of the peaks of all spectrum components, peakshaving a spectral intensity above a predetermined threshold value, orthe average value, the sum or the maximum value of the peak values ofall or a portion of the spectrum components.

(Further Exemplary Embodiment 8)

The image quality evaluation device according to any of Furtherexemplary embodiment 1 through Further exemplary embodiment 7, furtherincluding a photography device.

(Further Exemplary Embodiment 9)

The image quality evaluation device according to any of Furtherexemplary embodiment 1 through Further exemplary embodiment 8, furtherincluding a display device for displaying the periodic pattern to enableshooting.

(Further Exemplary Embodiment 10)

The Image Quality Evaluation Device According To Further ExemplaryEmbodiment 9, wherein the display device displays a pattern with amoving background superimposed on the periodic pattern.

(Further Exemplary Embodiment 11)

An image quality evaluation method for evaluating the quality of animage obtained by shooting a photographic subject including a periodicpattern that fluctuates periodically in one direction, wherein the imagequality evaluation method includes:

a Fourier transform process that accomplishes a two-dimensional Fouriertransform on the image to obtain two-dimensional spatial frequencyspectrum components; and

an analysis process that, among the two-dimensional spatial frequencyspectrum components obtained in the Fourier transform process, analyzesthe resolution of the image on the basis of spectrum components ofspatial frequencies included in the periodic pattern, and analyzes thedeterioration of the image on the basis of spectrum components otherthan these.

(Further Exemplary Embodiment 12)

A computer-readable recording medium for storing a program forevaluating the quality of an image obtained by shooting a photographicsubject including a periodic pattern that fluctuates periodically in onedirection, this program causing a computer to function as:

a Fourier transform means that accomplishes a two-dimensional Fouriertransform on the image to obtain two-dimensional spatial frequencyspectrum components; and

an analysis unit means, among the two-dimensional spatial frequencyspectrum components obtained by the Fourier transform means, analyzesthe resolution of the image on the basis of spectrum components ofspatial frequencies included in the periodic pattern, and analyzes thedeterioration of the image on the basis of spectrum components otherthan these.

(Further Exemplary Embodiment 13)

An image quality evaluation device for evaluating the quality of animage obtained by shooting a photographic subject including a periodicpattern that fluctuates periodically in one direction, wherein the imagequality evaluation device includes:

a Fourier transform means that accomplishes a two-dimensional Fouriertransform on the image to obtain two-dimensional spatial frequencyspectrum components; and

an analysis means that, among the two-dimensional spatial frequencyspectrum components obtained by the Fourier transform means, analyzesthe resolution of the image on the basis of spectrum components ofspatial frequencies included in the periodic pattern, and analyzes thedeterioration of the image on the basis of spectrum components otherthan these.

INDUSTRIAL APPLICABILITY

The present invention is suitable for analysis and evaluation of images.

What is claimed is:
 1. An image quality evaluation device for evaluatingthe quality of an image digitally compressed by a prescribed method andobtained by shooting a photographic subject including a periodic patternthat fluctuates periodically in one direction, wherein the image qualityevaluation device includes: a Fourier transform unit that accomplishes atwo-dimensional Fourier transform on the image to obtain two-dimensionalspatial frequency spectrum components; and an analysis unit that, amongthe two-dimensional spatial frequency spectrum components obtained bythe Fourier transform unit, analyzes the resolution of the image on thebasis of spectrum components of spatial frequencies included in theperiodic pattern, and analyzes the deterioration of the image on thebasis of spectrum components other than these, wherein the analysis unitdetermines whether or not the image has deteriorated through the digitalcompression process according to a position where a peak of the spectrumcomponents of the spatial frequencies corresponding to blocks that arecompression units of the digital compression.
 2. The image qualityevaluation device according to claim 1, wherein: the periodic patternhas a square wave shape; and the analysis unit analyzes the resolutionof the image on the basis of spectrum components relating to a firstdirection corresponding to the direction in which the periodic patternperiodically fluctuates, and analyzes deterioration of the image on thebasis of spectrum components relating to a second direction orthogonalto the first direction.
 3. The image quality evaluation device accordingto claim 2, wherein: the analysis unit analyzes the resolution of theimage and deterioration of the image on the basis of the peaks of allspectrum components, peaks having a spectral intensity above apredetermined threshold value, or the average value, the sum or themaximum value of the peak values of all or a portion of the spectrumcomponents.
 4. The image quality evaluation device according to claim 2,further comprising a display device for displaying the periodic patternto enable shooting.
 5. The image quality evaluation device according toclaim 1, wherein: the analysis unit analyzes the resolution of the imageand deterioration of the image on the basis of the peaks of all spectrumcomponents, peaks having a spectral intensity above a predeterminedthreshold value, or the average value, the sum or the maximum value ofthe peak values of all or a portion of the spectrum components.
 6. Theimage quality evaluation device according to claim 1, further comprisinga photography device.
 7. The image quality evaluation device accordingto claim 6, further comprising a display device for displaying theperiodic pattern to enable shooting.
 8. The image quality evaluationdevice according to claim 7, wherein the display device displays apattern with a moving background superimposed on the periodic pattern.9. The image quality evaluation device according to claim 1, furthercomprising a display device for displaying the periodic pattern toenable shooting.
 10. The image quality evaluation device according toclaim 9, wherein the display device displays a pattern with a movingbackground superimposed on the periodic pattern.
 11. An image qualityevaluation method for evaluating the quality of an image digitallycompressed by a prescribed method and obtained by shooting aphotographic subject including a periodic pattern that fluctuatesperiodically in one direction, wherein the image quality evaluationmethod includes: a Fourier transform process that accomplishes atwo-dimensional Fourier transform on the image to obtain two-dimensionalspatial frequency spectrum components; and an analysis process that,among the two-dimensional spatial frequency spectrum components obtainedin the Fourier transform process, analyzes the resolution of the imageon the basis of the spectrum components of spatial frequencies includedin the periodic pattern, and analyzes the deterioration of the image onthe basis of spectrum components other than these, wherein the analysisprocess determines whether or not the image has deteriorated through thedigital compression process according to a position where a peak of thespectrum components of the spatial frequencies corresponding to blocksthat are compression units of the digital compression.
 12. Anon-transitory computer-readable recording medium for storing a programfor evaluating the quality of an image digitally compressed by aprescribed method and obtained by shooting a photographic subjectincluding a periodic pattern that fluctuates periodically in onedirection, this program causing a computer to function as: a Fouriertransform means that accomplishes a two-dimensional Fourier transform onthe image to obtain two-dimensional spatial frequency spectrumcomponents; and an analysis means that, among the two-dimensionalspatial frequency spectrum components obtained by the Fourier transformmeans, analyzes the resolution of the image on the basis of spectrumcomponents of spatial frequencies included in the periodic pattern, andanalyzes the deterioration of the image on the basis of spectrumcomponents other than these wherein the analysis means determineswhether or not the image has deteriorated through the digitalcompression process according to a position where a peak of the spectrumcomponents of the spatial frequencies corresponding to blocks that arecompression units of the digital compression.